a cluster based routing algorithm minimizing

International Journal of Wireless & Mobile Networks (IJWMN) Vol.9, No.4, August 2017

A CLUSTER BASED ROUTING ALGORITHM MINIMIZING ENERGY CONSUMPTION IN WSN Alaa Aadri and Najlae Idrissi University of Sultan Moulay Slimane, Faculty of Sciences and Techniques Information Processing Decision Support Laboratory P.B. 523, Beni Mellal, Morocco

ABSTRACT Wireless sensor networks are continually being developed and constitute a new emerging technology that extends to many applications, they represent a very interesting field in the Internet of objects (IoT) and in information and communication technologies based on the manipulation of information through sensor nodes with limited characteristics (low storage capacity, autonomous source of energy, limited power), however, sensor nodes face the problem of energy constraints in terms of limited battery lifetime that has become the major issue in these networks and which represents a challenge to their design and management In these networks generally called WSN, Clustering routing represents a critical task to ensure energy efficiency and to overcome the constraints of congestion, collision and packet loss through several techniques of cluster formation and CH elections that have been proposed in literature. In this paper, we survey the principal clustering routing protocols in the literature, we describe their main characteristics and features, we propose a new cluster-based algorithm and we present its efficiency when comparing to some existing energy efficient clustering routing protocols using different simulation parameters.

KEYWORDS WSN; IoT; Clustering; Energy efficiency; Data aggregation; performance analyzis

1. INTRODUCTION In recent years WSN have attracted a lot of attention and have become an integral part of our lives, they are used in many civil and military applications where nodes can be deployed to capture, store, process, and transfer the sensed data permanently or also between physical contexts and virtual universes to help in operational decision-making. Routing issues and the selforganization of the nodes in the network are the two most studied themes in literature aiming to minimize energy consumed in the operations of capturing, processing and sending information via radio waves and to guarantee the overall functioning of the network. Clustering is one of the most efficient routing techniques to overcome the constraints imposed by the WSN environment and to achieve energy balancing in the network aiming to organize the network in clusters where each member node sends its collected data to its CH via the low-power radio link, which then aggregates them and sends them to the base station. This topology saves energy since only Cluster-Heads that are elected periodically so as not to exhaust the batteries of certain nodes quickly compared to others can transmit to the base station or to the sink node. In the rest of this paper, section 2 gives brief state of the art of WSN, section 3 describes routing in WSN and a classification of the different routing protocols classes, section 4 presents our hierarchical routing protocol. And finally, section 5 shows simulation parameters and performance metrics we have used and presents results and discussions. DOI: 10.5121/ijwmn.2017.9405

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2. STATE OF THE ART OF WIRELESS SENSOR NETWORKS (WSN) 2.1. PRESENTATION OF WSN A wireless sensor network consists of a set of electronic devices (sensors) capable of measuring physical values, processing them and transmitting them to a control center via a base station. Each sensor contains essentially four main units:

Figure 1. Sensor node components

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Sensing unit: usually consisting of a physical capture device that capture measurements and convert them into analog signals and of Analog-Digital Converters (ADCs) that convert these analog signals into digital signals.

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Processing unit: controls the procedures that enable the node to collaborate with other nodes to perform the acquisition tasks and store the collected data.

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Communication module: composed of a transceiver enabling communication between the different nodes of the network via a radio communication medium.

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Battery: the single source of energy that is generally neither rechargeable nor replaceable, it represents the main constraint while designing routing protocols for sensor networks.

2.2. WSN APPLICATIONS Given their ability to monitor a variety of environmental phenomena including temperature, humidity, pressure, speed and direction of an object, ..., the WSN can be used in military application(Control, communication, calculation, intelligence, surveillance, recognition and targeting), in environment applications (control of environmental aspects that may affect crops, chemical and biological detection, pollution, fire, movements of species Animal health, etc.), in health application (integrated patient monitoring, and control of patients detect heartbeat and another for blood pressure), and in some commercial applications (interactive toys, monitoring of the equipment condition, control of products).

2.3. MODELIZATION OF WSN WSN can be modeled by a graph:

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Where V represents the set of sensor nodes and E models all connections between these nodes. According to the organization of sensors in the deployment field, WSN can be presented under two main topologies: • Flat topology: all the nodes are homogeneous and identical in terms of capacity and characteristics except the sink, which is responsible for the transfer of data collected to the end user. This topology allows high fault tolerance but it suffers from low scalability. •

Hierarchical topology: In this topology, nodes are divided into several levels of organization and responsibility. Clustering represents one of the most used methods; it aims to divide the network into clusters composed of a Cluster Head (CH) and its cluster members that transfer their collected data for aggregation and transmission to the base station (BTS). This topology increases the scalability of the system, but it causes Cluster Heads overload and an unbalance in the energy consumption on the network.

2.4. CONSTRAINTS OF WSN Due to their specific characteristics, the factors that influence WSN factors that influence the design of WSN can be summarized as follows: •

Fault tolerance: the ability to maintain network functionality without interruptions in the presence of faults, this property R (t) is modelled in [1] by a Poisson distribution where R (t) gives the probability of not having a failure for a sensor node during the time interval [0, t].

Where λk is the failure rate of the sensor node k, and t is the period of time. •

Scaling factor: monitoring of a phenomenon may require the deployment of a high number of nodes (hundreds or even thousands of sensors). The network must be able to exploit the highly dense nature of some applications. A large number of nodes deployed in an application generates many transmissions and may impose difficulties for data transfer. The density can be calculated as follows:

Where N is the number of sensor nodes deployed in region A, and R is the transmission range. Μ (r) then gives the number of nodes in the transmission range R of a given node in region A. •

Deployment environment: due to the large number of nodes, it is difficult to configure them one by one. Therefore they must be able to self-organize themselves in order to route data to each other or to the Sink.

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Network topology: deployment, post-deployment (sensors can move or no longer operate) and redeployment of additional nodes to replace those that are defective or to meet the needs of tasks assigned to the network. This addition leads to the reorganization of the network and to the change of its topology

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Transmission media: since the nodes are connected by a wireless architecture and in order to enable operations on these networks, the transmission media must be standardized. Infrared, Bluetooth and Zig Bee radio communications are most commonly used.

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Energy consumption: the lifetime of a sensor depends essentially on the life of the battery. The energy consumed by a sensor is mainly due to the following operations: detection, processing and communication.

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Limited physical security: WSN are based on wireless communications, therefore they are more vulnerable to attacks on the transmitted data. The conventional techniques used to deal with these attacks are not applicable in WSN due to their resource limitations (computing power and memory).

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2.5. ENERGY CONSUMPTION MODEL FOR COMMUNICATION IN WSN In the literature, an energy consumption model was proposed in [Heinzelman & al, 2000] (Figure 2.) to describe the energy consumed by the sensors in each operation: the emission energy consumed to capture data and the communication energy that groups the transmission energy and the reception energy:

Figure 2. WSN Energy Consumption Module

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Transmitting energy: to transmit a message of k bits to a receiver far from d meters, the transmitter consumes:

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Reception energy: to receive a message of k bits the receiver consumes:

Where energy.

represents the electronic transmission energy and

represents the amplification

Both transmission and reception energies are determined by the amount of data to be communicated, by the transmission distance and by the physical properties of the radio module.

2.5. RADIO MODULE STATUS The radio module is the component that ensures communication between the nodes of the network and therefore it consumes the big part of energy, It can have four states: active, reception, transmission and sleep: •

Active state: the radio is on but the sensor node is neither receiving nor transmitting. This state causes a loss of energy due to unnecessary listening of the transmission channel.

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Sleep status: the radio is turned off.

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Transmission status: the radio transmits a packet.

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Receiving status: the radio receives a packet.

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3. ROUTING IN WSN Data routing designs the way how information is routed to its destination through a network connection, it consists on optimal packets delivering through the network using the least possible resources and ensuring network fault tolerance. In this part, we present a classification of WSN routing protocols with a focus on those based on the network hierarchization and on which a performance study will be applied in the next part of this article.

3.1. CLASSIFICATION OF WSN ROUTING PROTOCOLS Data Routing have attracted a lot of interest among the researchers, many routing protocols have been presented depending on type of application and on data routing strategies.

Figure 3. WSN Routing protocols classification

As shown in Figure 3. WSN routing protocols in WSN can be divided to: •

Negotiation-based routing: routes selection is based on the available resources to eliminate the redundancy of data in the network.

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Multipath-based routing: multi paths are used rather than single paths, which increases the fault tolerance but also energy consumption and traffic generation.

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Query-based routing: the destination node propagates a request for particular information in the network and the nodes possessing it respond by sending it to the requesting node.

• QOS-based routing: QoS-aware protocols consider end-to-end delay requirements while setting up the routes in the sensor network. • Coherent-based routing: forwards data after processing and redundancies elimination to the aggregator nodes in order to improve energy efficiency •

Flat-based routing: In this routing scheme nodes are identical (in terms of battery and hardware complexity), the disadvantage is that scalability becomes critical for a very large number of sensor nodes, hence the need to manage and organize the nodes using access control medium (MAC). Location-based routing: uses location information to guide route discovery and data transmission. It allows an optimized routing at reduced cost but the disadvantage is that each node must know the location of the other nodes of the network.

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3.2. HIERARCHICAL ROUTING IN WSN Hierarchical-based routing represents one of the most efficient strategy to improve energy efficiency and to achieve self-organization of the network. Several routing strategies have been proposed in the literature, in this paper we focus on the following energy efficient hierarchical routing protocols: 3.2.1. LEACH (Low-Energy Adaptive Clustering Hierarchy) This protocol was proposed by ChandraKasan & al. to provide an efficient solution to the problem of energy consumption in the WSN.

Figure 4. Scheme of LEACH protocol

LEACH is based on the formation of clusters in which the elected CHs collect and aggregate the data captured by their cluster member nodes to subsequently transmit them to the base station, a CH performs its role as cluster leader for a period of time called "round", at the beginning of each round each node of the network determines whether it wants to be a CH by calculating a number between 0 and 1 if this number is less than a threshold T (n) the node becomes CH, the threshold T (n) is expressed by the relation:

With p: the percentage of CHs in the network; r: the number of the current round; G: the number of nodes that have not been selected as CHs in the previous 1 / p rounds. Once the clusters are formed, each CH sends its identifications to the nodes of the network through the CSMA protocol and assigns to each member node of its cluster an interval of time during which it can send its data based on the TDMA approach. 3.2.1. PEGASIS (Power-Efficient Gathering In Sensor Information Systems) This routing protocol is considered as an optimization of LEACH, it gathers the network nodes in a long chain based on the principle that a node can communicate only with the closest node to it. Thus, each node adjusts its radio for a very short communication to conserve its energy. To communicate with the Sink, the process is organized into rounds; during each round a single node is allowed to communicate directly with the sink. This privilege is granted to all the nodes of the network in turn. A better conservation of energy is obtained by the data aggregating on each node 54


of the network: in each round, only one node can communicate directly with the sink, it’s called “leader node”, this privilege is given in turn to all the nodes of the network. Nodes transmit their data throw their neighboring nodes toward the leader node that sends it afterward to the base station.

Figure 5. Chain construction in PEGASIS

3.2.3. HEED (Hybrid Energy-Efficient Distributed Clustering) This protocol aims to divide the network into one hop clusters jump where CHs are elected according to two metrics: energy and cost of paths, each node calculates its probability to become CH by the following formula:

Where represents the remaining energy of the node and Inversely proportional to always greater than a threshold

its initial energy.

is

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A node of the network can be presented under two states: "tentative status" if